Under conventional approaches, manufacturing process defects are periodically recorded. For example, hundreds, or even thousands, of defects may be recorded daily for a particular manufacturing process, such as the construction of cargo ships or other manufactured goods. Typically, defects are stored in a database which can be accessed by quality engineers or other users. However, existing technologies are insufficient to efficiently manage such large numbers of defects. As a result, defects are often improperly identified or handled, and root causes of defects are often never identified. Although defect information may be digitized and stored in databases, these databases lack sufficient rules-based systems for identifying relationships between defects and identifying larger process issues to which the identified defects may belong.
These and other drawbacks exist with conventional defect management systems.